Generalized Reference Signaling Scheme for MU-MIMO Using Arbitrarily Precoded Reference Signals

ABSTRACT

A multi-user MIMO downlink beamforming system ( 200 ) is provided to enable transmit beamforming vectors to be efficiently provided to a subset of user equipment devices ( 201. i), where spatial separation or zero-forcing transmit beamformers (w i ) are computed at the base station ( 210 ) and used to generate precoded reference signals ( 216 ). The precoded reference signals ( 216 ) are fed forward to the user equipment devices ( 201. i) which apply one or more hypothesis tests ( 207. i,  208. i) to the precoded reference signals to extract the precoding matrix (W), including the specific transmit beamforming vector (w UE ) designed for the user equipment, and this extracted information is used to generate receive beamformers (v i ).

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is directed in general to the field of informationprocessing. In one aspect, the present invention relates to a system andmethod for communicating reference signal information in wireless MIMOcommunication systems.

2. Description of the Related Art

Wireless communication systems transmit and receive signals within adesignated electromagnetic frequency spectrum, but the capacity of theelectromagnetic frequency spectrum is limited. As the demand forwireless communication systems continues to expand, there are increasingchallenges to improve spectrum usage efficiency. To improve thecommunication capacity of the systems while reducing the sensitivity ofthe systems to noise and interference and limiting the power of thetransmissions, a number of wireless communication techniques have beenproposed, such as Multiple Input Multiple Output (MIMO), which is atransmission method where a transmitter having multiple transmitantennas wirelessly transmits signals to a plurality of receivers, eachof which has multiple receive antennas. For example, space divisionmultiple access (SDMA) systems can be implemented as closed-loop systemsto improve spectrum usage efficiency. SDMA has recently emerged as apopular technique for the next generation communication systems. SDMAbased methods have been adopted in several current emerging standardssuch as IEEE 802.16 and the 3rd Generation Partnership Project (3GPP)Long Term Evolution (LTE) platform.

FIG. 1 depicts a wireless MIMO communication system 100 that employsSDMA. In MIMO systems, transmitters and receivers are both equipped withmultiple antennas. The wireless communication system 100 includes one ormore transmitters 101 (e.g., base stations) and one or more receiverstations 102.1-102.m (e.g., subscriber stations), where “m” is aninteger representing the number of receiver stations in a givengeographic area. Base stations and subscriber stations can be bothtransmitters and receivers when both base stations and subscriberstations are equipped with a receiver and a transmitter. Base stationsgenerally communicate with multiple subscriber stations. Subscriberstations communicate directly with a base station and indirectly, viathe base station, with other subscriber stations. The number of basestations depends in part on the geographic area to be served by thewireless communication system 100. Subscriber systems can be virtuallyany type of wireless one-way or two-way communication device such as acellular telephones, wireless equipped computer systems, and wirelesspersonal digital assistants. The signals communicated between basestations and subscriber stations can include voice, data, electronicmail, video, and other data, voice, and video signals.

In an SDMA-MIMO wireless communication system, each base station 101 andsubscriber station 102.i includes an array of antennas for transmittingand receiving signals. In SDMA, different subscriber stations share thesame time-frequency channel and the separation between them occurs inthe spatial dimension. During transmission, the antenna array forms abeam or multiple beams by applying a set of transmit beam formingweights to signals applied to each antenna in the antenna array. Adifferent set of transmit beam forming weights is applied by the basestation to each communication with each subscriber station with a goalof minimizing interference between the radio communication devicessignals. In some transmission schemes, such as time division duplex(TDD), beam forming between the base station and subscriber stationsallows the allocation of the same frequency channel and different timechannel to subscriber stations during downlink and uplink. In othertransmission schemes, such as frequency division duplex (FDD), beamforming between the base station and subscriber stations allows theallocation of the same time channel and different frequency channel tosubscriber stations during downlink and uplink.

As depicted more specifically in FIG. 1, the MIMO system base station101 uses beamforming to transmit a single data stream (e.g., s₁) throughmultiple antennas, and the receiver combines the received signal fromthe multiple receive antennas to reconstruct the transmitted data. Thisis accomplished with “beamforming” weights whereby a signal s_(i) isprocessed in a signal processing unit 103.i for transmission by applyinga weight vector w_(i) to the signal s_(i) and transmitting the resultx_(i) over an array of antennas. The weighting vector w_(i) is used todirect the signal with the objective of enhancing the signal quality orperformance metric, like signal-to-interference-and-noise ratio (SINR)of the received signal. At the receiver, the received signals detectedby the array of antennas are processed using a combining vector v_(i).In particular, the base station 101 has an array of N antennas 105,where N is an integer greater than or equal to m. The base stationprepares a transmission signal, represented by the vector x_(i), foreach signal s_(i), where i∈{1, 2, . . . , m}. (Note: lower case boldvariables indicate vectors and upper case BOLD variables indicatematrices). The transmission signal vector x_(i) is determined inaccordance with Equation [1]:

x _(i) =w _(i) ·s _(i)  [1]

where w_(i), is the i^(th) beamforming, N dimensional transmissionweight vector (also referred to as a “transmit beamformer”), and eachcoefficient w_(j) of weight vector w_(i) represents a weight and phaseshift on the j^(th) transmit antenna 105. In addition, the term “s_(i)”is the data to be transmitted to the i^(th) receiver. Each of thecoefficients of weight vector w_(i) may be a complex weight. Unlessotherwise indicated, transmission beamforming vectors are referred to as“weight vectors,” and reception vectors are referred to as “combiningvectors,” though in systems having reciprocal channels (such as TDDsystems), a combining vector v at a receiver/subscriber station can beused as both a combining vector (when receiving signals from atransmitter/base station) and a weighting vector (when transmitting to atransmitter/base station).

The transmission signal vector x_(i) is transmitted via a channelrepresented by a channel matrix H_(i). The channel matrix H_(i)represents a channel gain between the transmitter antenna array 105 andthe receive antenna array 104.i at the i^(th) subscriber station 102.i.Thus, the channel matrix H_(i) can be represented by a N×k_(i) matrix ofcomplex coefficients, where N is the number of antennas at the basestation antenna array 105 and k_(i) is the number of antennas in thei^(th) subscriber station antenna array 104.i. The value of k_(i) can beunique for each subscriber station. As will be appreciated, the channelmatrix H_(i) can instead be represented by a k_(i)×N matrix of complexcoefficients, in which case the matrix manipulation algorithms areadjusted accordingly so that, for example, the right singular vectorcalculation on a N×k_(i) channel matrix becomes a left singular vectorcalculation on a k_(i)×N channel matrix. The coefficients of the channelmatrix H_(i) depend, at least in part, on the transmissioncharacteristics of the medium, such as air, through which a signal istransmitted. A variety of methods may be used to determine the channelmatrix H_(i) coefficients, such as transmitting a known pilot signal toa receiver so that the receiver, knowing the pilot signal, can estimatethe coefficients of the channel matrix H_(i) using well-known pilotestimation techniques. Alternatively, the actual channel matrix H_(i) isknown to the receiver and may also be known to the transmitter.

At the subscriber station 102.i, the transmitted signals are received onthe k_(i) receive antennas. For example, the transmission signal vectorx₁ is transmitted via a channel represented by a channel matrix H₁, andis received at the receiver 102.1 as a receive signal vector y₁=H₁^(H)x₁+n₁ (where n represents noise and any co-channel interferencecaused by other subscriber stations). More specifically, the receivedsignals for the i^(th) subscriber station 102.i are represented by ak_(i)×1 received signal vector y_(i) in accordance with Equation [2]:

$\begin{matrix}{y_{i} = {{s_{i}^{*}H_{i}^{H}w_{i}} + \left( {{\sum\limits_{n = 1}^{m}\; {s_{n}^{*}H_{i}^{H}w_{n}}} - {s_{i}^{*}H_{i}^{H}w_{i}}} \right)}} & \lbrack 2\rbrack\end{matrix}$

where “s_(i)” is the data to be transmitted to the i^(th) subscriberstation 102.i, “s_(n)” is the data transmitted to the n^(th) subscriberstation 102.n, the * superscript denotes the complex conjugationoperator, “H_(i) ^(H)” represents the complex conjugate transpose of thechannel matrix correlating the base station 101 and i^(th) subscriberstation 102.i, w_(i) is the i^(th) transmit weight vector, and w_(n) isthe n^(th) transmit weight vector. The superscript “H” is used herein asa hermitian operator to represent a complex conjugate transposeoperator. The j^(th) element of the received signal vector y_(i)represents the signal received on the j^(th) antenna of subscriberstation 102.i, j∈{1, 2, . . . , k_(i)}. The first term on the right handside of Equation [2] is the desired receive signal while the summationterms less the desired receive signal represent co-channel interference.Finally, to obtain a data signal, z_(i), which is an estimate of thetransmitted data s_(i), a signal processing unit 108.i at the subscriberstation 102.i combines the signals received on the k antennas using acombining vector v_(i) in accordance with Equation [3]:

z _(i) =ŝ _(i) =y _(i) ^(H) v _(i).  [3]

While the benefits of MIMO are realizable when the receiver 102.i aloneknows the communication channel, these benefits are further enhanced in“closed-loop” MIMO systems when the transmitter 101 has some level ofknowledge concerning the channel response between each transmitterantenna element and each receive antenna element of a receiver 102.i.Precoding systems provide an example application of closed-loop systemswhich exploit channel-side information at the transmitter (“CSIT”). Withprecoding systems, CSIT can be used with a variety of communicationtechniques to operate on the transmit signal before transmitting fromthe transmit antenna array 105. For example, precoding techniques can beused at the base station 101 to provide a multi-mode beamformer functionto optimally match the input signal on one side to the channel on theother side so that multiple users or subscriber stations can besimultaneously scheduled on the same time-frequency resource block (RB)by separating them in the spatial dimension. This is referred to as aspace division multiple access (SDMA) system or as a multi-user(MU)-MIMO system. Additional examples of precoding include using achannel quality indicator (CQI) value measured at a receiver 102.i toperform adaptive modulation and coding (AMC) on the transmit signalbefore transmission to the receiver 102.i.

While full broadband channel knowledge may be obtained at thetransmitter 101 by using uplink sounding techniques (e.g., with TimeDivision Duplexing (TDD) systems), most precoded MIMO systems (e.g.,with TDD or Frequency Division Duplexing (FDD) systems) use channelfeedback techniques to measure channel information at the receiver 102.iand then feed back the measured channel information to the transmitter101. However, it is difficult to accurately measure the channelinformation or associated channel characteristics (such as SINR orchannel quality information (CQI)) for a particular receiver when thecommunication status of other receivers in the vicinity is not known. Inan SDMA system, the incomplete knowledge at a receiver results from thefact that signal information being sent to other receivers can appear asinterference or noise at the intended receiver 102.i, though thereceiver can not be expected to have this knowledge when the channelcharacteristics are being measured. To address the fact that eachreceiver station has incomplete knowledge about the transmissionconditions when the channel information is being measured, thetransmitter station 101 can feed forward the precoding matrixinformation W=[w₁, w₂, . . . w_(m)] that is computed based on thechannel feedback information from the receiver stations 102.1-102.m.However, the signaling overhead associated with feeding forward theprecoding matrix information to each receiver station can be quitelarge, especially when the precoding matrix information can bearbitrarily computed as a function of the channel vector feedbackinformation from each receiver station. Moreover, the limited feedforward resources require that any practical system be designed to havea low feed forward rate, while existing systems for feeding forwardprecoding matrix information can have unacceptably high feed forwarddata rates. Dedicated reference signals can be used whereby one or morereference signals are weighted and transmitted using the same transmitbeamforming vectors as the beamformed data signals. However, dedicatedreference signals typically require a significant signaling overhead fornotifying each receiver of its dedicated reference signal, such ascontrol signals to indicate the number of precoded streams and thedesired reference signal for each receiver. Even if the signalingoverhead is included as part of the usual scheduling overhead, it stillconsumes valuable overhead.

Accordingly, there is a need for an improved system and methodology forsignal processing and control signaling in a MIMO-SDMA system. There isalso a need for a multi-user MIMO system which efficiently conveysprecoding matrix information to a particular receiver without requiringadvance knowledge of the other receivers or the base station schedulingalgorithm. In addition, there is a need for a family of signalprocessing algorithms for generating transmit and receive array vectorsfor MIMO-SDMA which overcomes limitations in the feed forward data rateand other problems in the art, such as outlined above. Furtherlimitations and disadvantages of conventional processes and technologieswill become apparent to one of skill in the art after reviewing theremainder of the present application with reference to the drawings anddetailed description which follow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may be understood, and its numerous objects,features and advantages obtained, when the following detaileddescription of a preferred embodiment is considered in conjunction withthe following drawings, in which:

FIG. 1 (labeled prior art) depicts a wireless communication system;

FIG. 2 depicts a wireless communication system in which precodedreference signals are fed forward to convey downlink transmitbeamforming matrix information to each receiver station;

FIG. 3 depicts a first example flow for a precoding methodology forgenerating and feeding forward precoded reference signal information toone or more user equipment devices;

FIG. 4 depicts an example flow for a generalized reference signalingscheme for a multi-user MIMO system using arbitrarily precoded referencesignals; and

FIG. 5 depicts an example flow for a generalized reference signalingscheme for a multi-user MIMO system using a single precoded referencesignal.

DETAILED DESCRIPTION

A reference signal feed forward system and methodology are described foruse in efficiently providing precoding matrix information to receiversin a wireless, multi-user, multi-input, multiple output (MIMO) SDMAsystem. Once a transmitter (e.g., base station) generates precodingvectors using an arbitrary multi-user MIMO beamforming algorithm,precoded reference signals are fed forward to some or all of thereceivers (e.g., user equipment devices) to provide knowledge of theprecoding vectors to the receiver(s). Dedicated precoded referencesignals are used whereby one or more reference signals are weighted andtransmitted using the same transmit beamforming vectors as thebeamformed data signals. However, dedicated reference signals typicallyrequire a significant signaling overhead for notifying each receiver ofits dedicated reference signal, such as control signals to indicate thenumber of precoded streams and the desired reference signal for eachreceiver. Even if the signaling overhead is included as part of theusual scheduling overhead, it still consumes valuable overhead. At thereceiver, the precoded reference signals are processed with one or morehypothesis tests to extract the beamforming vectors and/or matrixinformation which enables receive beamformers to be designed for thereceiver, such as by using, for example, a minimum mean square error(MMSE) criterion. In selected embodiments, a first test is performed atthe receiver to process the precoded reference signals to detect whichof the precoded reference signals was intended for the receiver inquestion without the need of feed forwarding explicit information tothat effect. With a second test, the receiver processes the precodedreference signals to identify all of the precoding vectors W=[w₁, w₂, .. . w_(m)] used by the transmitter, thereby facilitating MMSE decodingat the receiver. In this way, a generalized reference signaling schemeis enabled for a MU-MIMO system using arbitrarily precoded referencesignals.

Various illustrative embodiments of the present invention will now bedescribed in detail with reference to the accompanying figures. Whilevarious details are set forth in the following description, it will beappreciated that the present invention may be practiced without thesespecific details, and that numerous implementation-specific decisionsmay be made to the invention described herein to achieve the devicedesigner's specific goals, such as compliance with process technology ordesign-related constraints, which will vary from one implementation toanother. While such a development effort might be complex andtime-consuming, it would nevertheless be a routine undertaking for thoseof ordinary skill in the art having the benefit of this disclosure. Forexample, selected aspects are shown in block diagram form, rather thanin detail, in order to avoid limiting or obscuring the presentinvention. In addition, some portions of the detailed descriptionsprovided herein are presented in terms of algorithms or operations ondata within a computer memory. Such descriptions and representations areused by those skilled in the art to describe and convey the substance oftheir work to others skilled in the art. Various illustrativeembodiments of the present invention will now be described in detailbelow with reference to the figures.

FIG. 2 depicts a wireless communication system 200 in which N precodedreference signal(s) 216 are fed forward from a transmitter 210 (e.g., abase station) to one or more receivers 201.1-m (e.g., subscriberstations) to convey downlink transmit beamforming matrix information toeach receiver station 201.i. The transmitter 210 includes an array 226of antennas for communicating with the receivers 201.1 through 201.m,each of which includes an array 202.i of receive antennas forcommunicating with the transmitter 210. In operation, a data signals_(i) presented at the transmitter 210 for transmission to the receiver201.i is transformed by the signal processor 224.i into a transmissionsignal represented by the vector x_(i). The signals transmitted from thetransmit antenna 226 propagate through a matrix channel H_(i) and arereceived by the receive antennas 202.i where they are represented by thevector y_(i). For a MIMO channel from the transmitter 210 to the i^(th)receiver 201.i, the channel is denoted by H_(i), i∈{1, 2, . . . , m}.The channel matrix H_(i) may be represented as an N×k matrix of complexentries representing the complex coefficients of the transmissionchannel between each transmit-receive antenna pair, where N representsthe number of transmit antennas in the transmit antenna array 226, andk_(i) represents the number of antennas of the i^(th) receiver 201.i (orvice versa). At the receiver 201.i, the signal processing unit 203.iprocesses the y_(i) signals received on the k antennas to obtain a datasignal, z_(i), which is an estimate of the transmitted data signals_(i). The processing of the received y_(i) signals may includecombining the y_(i) signals with appropriate combining vectorinformation v_(i) generated by the minimum mean square error (MMSE)receiver design module 209.i. As described herein, the receiver 201.iuses the precoded reference signals to extract the transmit beamformingvector matrix information W generated at the transmitter 210, and thenuses the extracted transmit beamforming vector matrix information W tocompute or choose the combining vector information v_(i) using anydesired receive beamformer design method, for example the MMSE method.

Transmit beamforming or precoding at the transmitter may be implementedby having each receiver 201.i determine its MIMO channel matrixH_(i)—which specifies the transmission channel between a transmitter andan i^(th) receiver—in the channel estimation signal processing unit203.i. For example, in a MIMO implementation, each receiver 201.1-mdetermines its MIMO channel matrix H_(i) by using pilot estimation orsounding techniques to determine or estimate the coefficients of thechannel matrix H_(i). Each receiver 201.i uses the estimated MIMOchannel matrix or other channel-related information (which can bechannel coefficients or channel statistics or their functions, such as aprecoder, a beamforming vector or a modulation order) to generate orcompute an initial receive or combining beamforming vector v_(i). Forexample, a receive beamforming design module 204.i at each receiver201.i computes an initial or optimal receive beamforming vectorv_(opt i) that represents an optimal blind receive beamforming vector,such as by maximizing a predetermined receivesignal-to-interference-and-noise (SINR) metric. Alternatively, thereceive beamforming vector v_(opt i) for the receiver 201.i is derivedfrom or is generated to be substantially equivalent to a right singularvector corresponding to the maximum singular value of the channel matrixbetween the transmitter 210 and the receiver 201.i (e.g.,v_(opt i)=RSV_(max)(H_(i))). However computed, the initial beamformingvector v_(opt i) is used to generate effective channel information inthe design module 204.i, such as by computing or selecting a vectorcodeword u_(i) representing the vector quantity H v_(opt i). In selectedembodiments, the vector codeword u_(i) represents the preferredprecoding vector for the receiver 201.i, where the preferred precodingvector are the columns of on or more unitary matrices, which may bereferred to as basis vectors. As will be appreciated, each receiver201.i may compute and feed back other information in addition to, or inplace of effective channel information u_(i), such as channel qualityinformation (CQI) or any other information that may be used at thetransmitter to generate precoding matrix W information.

Rather than feeding back the entire scalar, vector or matrixrepresentation of the effective channel information (such as theselected codeword u_(i) or the full CQI values which would require alarge number of bits), the receiver 201.i may use a quantizer 205.i toquantize the effective channel information u=H_(i) v_(opt i) that isgenerated by the design module 204.i and that will be used by thetransmitter 210 in controlling signal transmission to the receiver201.i. For example, in quantizing the effective channel information u, afeedback codebook 211.i at the receiver 201.i may be used to store anindexed set of possible codewords u so that the codewords u generated bythe vector design module 204.i can be used by the quantizer 205.i toretrieve a corresponding index from the feedback codebook 211.i andprovide the retrieved index over a feedback channel 218.i (e.g., a lowrate feedback channel 215) to the transmitter 210.

Once the effective channel information from a receiver 201.i—such as theselected codeword u_(i) and CQI value(s)—are indexed and fed back to thetransmitter 210 over the low rate feedback channel 215, the transmitter210 decodes or dequantizes the indexed feedback information using acodebook-based dequantizer 220 which accesses a feedback codebook 221 toobtain the effective channel information (e.g., u_(i)) for the receiver201.i. As will be appreciated, the transmitter feedback codebook 221 isthe same as the feedback codebook 211.i used at the receiver 201.i. Theretrieved effective channel information is provided to the design module222 which computes scheduling information and designs the transmitbeamforming vectors w_(i) for each receiver 201.i When the selectedcodeword u_(i) computed by the receiver 201.i represents the receiver'seffective channel, u_(i)=H_(i)v_(i)/∥H_(i)v_(i)∥, the design module 222at the transmitter 210 may use a spatial separation algorithm such aszero-forcing beamforming (ZFBF) (or variants thereof such as regularizedzero-forcing beamforming) to design each transmit beamforming vectorw_(i)={tilde over (w)}/∥{tilde over (w)}_(i)∥ such that

{tilde over (w)} _(i) ^(H) u _(j)≧γ₁, if i=j

{tilde over (w)} _(i) ^(H) u _(j)≦γ₂, if i≠j  [4]

where γ₁>0 and γ₂ are constants such that γ₂<<γ₁. Usually, γ₂≈0.Equation 4 is a typical spatial separation constraints equation thatensures that the desired signal component is accentuated and theundesirable interference terms are minimized at the receiver. A specificembodiment of the above is the zero-forcing beamforming equation whereγ₁=1 and γ₂=0.

One approximate solution to the zero-forcing version of Equation 4 withγ₁=1 and γ₂=0 is given by:

{tilde over (W)}=X(X ^(H) X+αI)⁻¹  [5]

where X=[u₁u₂ . . . u_(k)], I is an identity matrix and α is a scalarconstant that provides a smoothing function to account for imperfectionsin the knowledge of the effective channel due to quantization orotherwise. The solution in Equation (5) is exact with respect toEquation (4) if α=0. This ensures that interference to a user due to theother users' transmissions is close to zero. In selected embodiments,the designed precoding vectors w_(i) are computed as a function of thepreferred precoding vectors requested by the receivers. However, whilezero-forcing beamforming can be used to generate a beamforming matrixW=[w₁, w₂, . . . w_(m)] 223, it will be appreciated that the designmodule 222 can use any (arbitrary) multi-user MIMO algorithm to generatethe beamforming matrix information W 223. In accordance with variousembodiments, the designed transmit beamforming vectors are selected froma defined set of candidate transmit beamforming vectors which are alsoknown to the receivers 201.i, even though any given receiver has noadvance knowledge about which transmit beamforming vector is intendedfor which receiver.

Once the design module 222 designs the transmit beamforming vectors wifor each receiver 201.i, the design module 222 provides the designedtransmit beamforming vectors wi contained in the precoding information223 to one or more signal processors 224.i where they are applied toprecode the data input signal si in the course of generating thetransmit signal xi which is transmitted over the transmit antenna array226 to the receiver(s) 201.i.

Before using the precoding information to control signal transmission tothe receivers 201.i, the transmit beamforming vectors w_(i) may beassembled in the form of a beamforming matrix W=[w₁, w₂, . . . w_(m)]and conveyed to the receivers by either (a) using reference signalscarrying precoded pilot symbols, or (b) sending bit(s) on the controlchannel indicative of the transmission matrix W.

When conveyed by using one or more reference signals, the beamformingmatrix W is used by the encoder module 225 in the reference signalgenerator 228 to generate up to N precoded reference signal(s) 216 thatmay be fed forward to the receivers 201.i. In various embodiments, theprecoded reference signals may refer to one or more (up to N) precodedreference signals, depending on how the transmit beamforming matrix isencoded and received. In this way, the transmitter 210 transmits one ormore precoded reference signals corresponding to either the transmitbeamforming matrix or to one or more of of its computed transmitbeamforming vectors. For example, if the transmitter antenna array 226has four transmit antennas, up to four receivers can be simultaneouslysupported when zero-forcing beamforming is used. In this case, up tofour reference signals (e.g., RS₁, RS₂, RS₃, and RS₄) are precoded withprecoding vectors (e.g., w₁, w₂, w₃, and w₄), thereby generating up tofour precoded reference signals (e.g., RS₁w₁, RS₂w₂, RS₃w₃, and RS₄w₄).

When conveyed by using bit level signaling, the beamforming matrix W isfed forward to each receiver 201.i by sending bits 216 on the controlchannel that are indicative of the transmission matrix used. Thisapproach assumes that the transmission matrix W is chosen from a set ofM possible candidate matrices so that each candidate matrix may beuniquely identified by a minimum of log₂(M) bits. To implement bit levelsignaling, a feed forward codebook 227 may be used to store each of thecandidate matrices with their corresponding bit index values. The bitindex that is representative of the transmission matrix W may betransmitted by the transmitter to each receiving device. And since thereceiving device has information of all possible candidate transmissionmatrices beforehand (e.g., stored in a feed forward codebook 212.i), thereceiving device can use the bit index to retrieve the appropriatetransmission matrix W by a single lookup, and can subsequently use thistransmission matrix W to design its receive beamformer. In oneembodiment, a bit sequence uniquely identifying the transmission matrixW above is transmitted and the receiver retrieves the transmissionmatrix W by employing a lookup into its database of candidatetransmission matrices. In an alternative embodiment, the transmitter andthe receiver can share beforehand a codebook of transmission vectors,and the final transmission matrix W used would be a combination of atmost N distinct transmission vectors. In such a case, the transmittermay signal the transmission matrix W by sending N K-bit sequences, whereeach sequence is uniquely representative of the transmission vectorscomprising the transmission matrix W, where K is the minimum number ofbits required to uniquely represent each candidate transmission vector.In yet another alternative embodiment, the transmitter may sent N bitsequences, each of which uniquely identifies the codewords that were fedback to the transmitter by each multiplexed user, where K is the minimumnumber of bits required to uniquely represent each candidatetransmission vector. In this case, the transmitter uses a pre-determinedalgorithm, which is known to all receiving units, to map the codewordsto the final transmission matrix W used. The receiver first retrievesthe codewords of all multiplexed users using the bit sequences fedforward to it by the transmitter, and then constructs the transmissionmatrix W using the known algorithm. The result of the execution ofeither of the embodiments above is the knowledge of the transmissionmatrix W at the receiver. Once the transmission matrix W is known, thereceiving unit executes a second test to determine which of thetransmission vectors contained in W is meant for it. In one embodiment,this test is done by computing max_(j=1,2, . . . ,N) |w_(j)^(H)Hv_(opt)|², where v_(opt) is the optimal blind receive beamformer, His the MIMO channel matrix and w_(j) is the jth column of W.

The precoded reference signals (RS₁w₁, RS₂w₂, . . . RS_(M)w_(M)) 216 maybe fed forward by the feed forward control field generator 229 over afeed forward channel 219.i (e.g., a low rate feed forward channel 215)to the receivers 201.i. Once the precoded reference signal information216 is fed forward to the receiver 201.i, the receiver 201.i decodes theinformation and provides the precoded reference signal information tothe beamforming matrix estimation module 206.i. For example, a feedforward control decoder (not shown) is used to decode the feed forwardsignal to obtain the precoded reference signal information generated bythe transmitter 210.

However recovered, the retrieved precoded reference signal informationis processed by the beamforming matrix estimation module 206.i to enableMMSE receive operations without having prior knowledge about whichspecific precoding vector w_(UE) was intended for the receiver or whichbeamforming algorithm was used by the transmitter 210 to generate theprecoding vectors w₁, w₂, . . . w_(m). In this way, the transmitter 210has complete flexibility in designing its beamforming matrix andprecoding algorithms. To provide this flexibility, the beamformingmatrix estimator 206.i processes the received precoded reference signalsto detect which exact precoding vectors w₁, w₂, . . . w_(m) were used bythe transmitter 210, and to detect which of the precoding vectors isintended for the receiver in question.

To detect this information from the precoded reference signals, thebeamforming matrix estimator 206.i performs hypothesis testing on thereceived precoded reference signals. With a first hypothesis test, theextraction module 207.i determines which reference signal, out of the‘m’ reference signals transmitted, is encoded using the transmissionvector intended for the receiver by effectively projecting the receivedprecoded reference signals to its optimal blind receive beamformer. Ineffect, the comparison function uses the received precoded referencesignals to determine which reference signal is intended for thereceiver. In an example implementation, the detection function appliesthe following test:

$\begin{matrix}{{\max\limits_{{j = 1},2,3,4}{{v_{opt}^{H}y_{j}}}^{2}},} & \lbrack 6\rbrack\end{matrix}$

where v_(opt) is the optimal blind receive beamformer initially designedby the receiver design module 204.i, y_(j) are the received N precodedreference signals (e.g., y_(j)=RS_(i)w_(i)), and H is the channel matrixto the receiver in question. For a given precoded reference signal y,the desired reference signal chosen is the one that maximizes the testdefined in Equation [6]. In effect, this test provides a measure of how“aligned” each precoding vector is with respect to the users effectivechannels. As a result, the precoded reference signals can be fed forwardto the receivers without also feeding forward explicit information toidentify which precoding vector was intended for the receiver.

In addition to detecting the intended reference signal, the beamformingmatrix estimator 206.i may also perform additional hypothesis testing onthe received precoded reference signals to extract the precoding matrixW used by the transmitter to facilitate MMSE decoding at the receiver.To this end, the extraction module 208.i applies a second hypothesistest to extract from a predetermined set the exact precoding vector usedto generate each precoding reference signal, thereby obtaininginformation of all precoded vectors generated by the transmitter. Ineffect, the extraction function tests each precoded reference signal toidentify which precoding vector from a predetermined set of precodingvectors was used to generate the precoded reference signal. In anexample implementation, the comparison function applies the followingtest:

min_(i)∥y−H ^(H) w _(i)∥²,  [7]

where y is the received precoded reference signal (e.g., y=RS₁w₁), H isthe channel matrix to the receiver in question, and w_(i) is used foreach of the predetermined set of precoding vectors (e.g., w₁, w₂, . . .w_(m)) stored at the receiver. For each precoded reference signal y, thetransmit beamformer w_(i) is chosen which minimizes the test defined inEquation [7]. In effect, this test provides a distance measure that isused to identify which precoding vector (e.g., w₁, w₂, . . . w_(m)) isthe beamforming vector w used to generate the precoded reference signal.Once each of the precoded reference signals are tested, the complete setof precoding vectors is identified, and as a result, the transmissionmatrix W is identified.

Upon extracting the complete set of precoding vectors (which may berepresented as a precoding matrix W), the beamforming matrix estimatorprovides this information to the MMSE receiver design module 209.i whichcomputes the adjusted combining vector v_(i) for the receiver 201.i. Theadjusted combining vector v_(i) is used by the receiver signalprocessing unit 203.i to process the y_(i) signals received on the kantennas to obtain a data signal, z_(i) by combining the y_(i) signalswith the adjusted combining vector information v_(i).

In an alternative embodiment, the transmission vector to receiver i,w_(i) may be chosen by the base station such that it can potentially beany vector in the N dimensional complex space—in such a case the test inEquation [7] cannot be applied since the set of possible precodingvectors is unknown at the receiver. Under such scenarios, the followingprocedure is used to design the receive beamformer. Let y_(j)(t), j=1,2,. . . , N denote the j^(th) reference signal at time t—suppose that kpilot time samples are sent per reference signal, that is t=1,2, . . .,k where k is greater than or equal to 1. First, using the firsthypothesis test in Equation [6], the receiver 201.i determines which ofthe N reference signals is meant for itself For example, we can assumethat a receiver 201.i determines that the y₁ reference signal isintended for the receiver 201.i. Once the intended reference signal isdetected, the MMSE receive beamformer is then designed using thefollowing function:

$\begin{matrix}{v_{MMSE} = {\left( {{\sum\limits_{j = 1}^{N}\; {\frac{1}{k}{\sum\limits_{t = 1}^{k}{{y_{i}(t)}{y_{i}(t)}^{H}}}}} + {\sigma_{n}^{2}I}} \right)^{- 1}\left( {\frac{1}{k}{\sum\limits_{t = 1}^{k}{y_{1}(t)}}} \right)}} & \lbrack 8\rbrack\end{matrix}$

where I is the identity matrix and σ_(n) ² is the white noise spectraldensity.

In another embodiment, the receive beamformer may be designed using thefollowing function:

$\begin{matrix}{v_{MMSE} = {\beta \; \max \; {{eig}\left\lbrack {\left( {{\sum\limits_{j = 1}^{N}\; {\frac{1}{k}{\sum\limits_{t = 1}^{k}{{y_{i}(t)}{y_{i}(t)}^{H}}}}} + {\sigma_{n}^{2}I}} \right)^{- 1}\left( {\frac{1}{k}{\sum\limits_{t = 1}^{k}{{y_{1}(t)}{y_{1}(t)}^{H}}}} \right)} \right\rbrack}}} & \lbrack 9\rbrack\end{matrix}$

where “max eig (X)” denotes the dominant eigen vector of the matrix X.

FIG. 3 depicts a generalized example flow for a precoding methodology300 for generating and feeding forward precoded reference signalinformation to one or more user equipment devices. As a preliminarystep, the MIMO transmission channel to a given receiver station isestimated by transmitting a pilot signal from the transmitter or basestation (step 302) to the receiver or user equipment where thetransmission channel is estimated (step 304). Generally, a transmissionchannel can be estimated by embedding a set of predetermined symbols,known as training symbols, at a base station and processing the trainingsymbols at the user equipment to produce a set of initial channelestimates. In this example, the MIMO transmission channel beingestimated at the user equipment may be characterized as a channel matrixH.

Based on the channel estimate information, the user equipment designs orcomputes an optimal blind receive beamforming vector v (step 306). Thismay be implemented by taking the singular value decomposition (SVD) ofthe MIMO channel matrix H=U Λ V^(H), where the matrix U is a leftsingular matrix representing the transmit signal direction, the matrix Λrepresents the strength (or gain) of the channel and the matrix V is aright singular matrix representing the receive signal direction. Theuser equipment also uses the channel estimate information H to computethe effective channel vector information (step 308), such as bycomputing or selecting a codeword u. The receive beamforming vector vand codeword u may be computed in a variety of different ways. Forexample, they may be designed by selecting the values v and u=Q(Hv) thatmaximize a predetermined performance metric, where Q(.) is somequantization function. However determined, the codeword u is indexed andfed back to the base station at step 310. As disclosed herein,codebook-based feedback indexing techniques may be used to quantize thecodeword u where the base station and user equipment share the samefeedback codebook.

At the base station, the feedback information from the user equipment isdequantized (step 312) into the effective channel vector information(e.g., codeword u). The dequantized effective channel vector informationis used by the base station to design the transmit beamforming vectorsw_(i) using any arbitrary multi-user MIMO beamforming algorithm (step314), such as a regularized ZFBF algorithm. The transmit beamformingvectors w_(i) may be represented as a beamforming matrix W=[w₁, w₂, . .. w_(m)]. As will be appreciated, the dequantized effective channelvector information may also be used to select an appropriate modulationand coding level in systems that implement adaptive modulation andcoding (AMC) mechanisms. Once the transmit beamforming vectors w_(i) aredesigned, the base station uses the vectors w_(i) to compute precodedreference signals (step 316), such as by precoding one or more referencesignals with the transmit beamforming vectors w_(i). In otherembodiments, the base station uses the vectors w_(i) to derive the bitindex values corresponding to the precoding matrix W formed from thevectors w_(i). The precoded reference signals (or the index bit values)are then fed forward to the user equipment as part of the downlink datatransmission (step 318), either directly or in quantized form using afeedforward codebook.

At the user equipment, the feed forward information is decoded to obtainthe precoded reference signals. As will be appreciated, the base stationand user equipment device(s) share the same feed forward codebook.However decoded, the precoded reference signals are tested to obtain theinformation needed to perform MMSE receive operations (step 320). Asdescribed herein, the testing consists of one or more hypothesis testswhich take into account the presence of Gaussian noise at the receiver.As a result, the robustness of the testing is directly a function of theadditive noise present and interference present.

In testing of the precoded reference signals, a first test (step 322) isused to extract the precoding vector w from the precoded referencesignals that is intended for the user equipment in question, but withoutrequiring that explicit information be fed forward to specify theintended precoding vector. In an example implementation, the intendedreference signal is identified from the precoded reference signals byselecting the precoding vector from a finite set of precoding vectors(e.g., w₁, w₂, w₃, w₄) which minimizes the distance measure

$\min\limits_{{j = 1},2,3,4}{{{v_{opt}^{H}{Hw}_{j}}}^{2}.}$

In a selected spatial separation algorithm embodiment, the firstextraction test 322 uses properties of zero-forcing type beamformingtechniques whereby, with the optimal receive beamformer v_(opt) used,the other precoding vectors will be substantially orthogonal to theequivalent channel H v_(opt).

The testing of the precoded reference signals may also include a secondtest (step 324) which extracts the precoding matrix W from the precodedreference signals by extracting from each precoded reference signal theprecoding vector w_(i) that was used to precode the precoded referencesignal, again without requiring that explicit information be fed forwardspecifying the precoding matrix W. In an example implementation, theprecoding matrix W is extracted from the precoded reference signals byselecting the precoding vector from a predetermined set of precodingvectors (e.g., w₁, w₂, . . . w_(m)) which minimizes the distancemeasure, min_(i)∥y−H^(H)w_(i)∥². The extracted precoding vectorinformation is used by the user equipment to design the receivebeamforming vectors v_(i) for the user equipment (step 326), such as byusing an MMSE receiver to derive the receive beamforming vectors v_(i).

Selected embodiments of the present invention may also be illustratedwith reference to FIG. 4, which depicts an example flow 400 for ageneralized reference signaling scheme for a multi-user MIMO systemusing arbitrarily precoded reference signals. As depicted, the processstarts (step 401) when the receiver station determines the transmissionchannel profile based on the estimated channel information for the MIMOtransmission channel (step 402). Based on the channel profileinformation, the receiver station designs its optimal blind receivebeamformer v and selects an optimal codeword u=Hv (step 404) torepresent the effective channel to the receiver station. In an exampleimplementation, the vectors u and v may be jointly designed by selectingcandidate values from a codebook of indexed precoding parameters thatmaximize a predetermined performance metric for estimating the receiveSINR, where the metric is defined to reduce quantization errorsresulting from the codebook-based selection process. To account for thefact that the receiver station does not have prior knowledge aboutpotential interference from other receiver stations, the receiverstation uses the computed vector v as an initial receive beamformingvector. After quantizing the optimal codeword u (such as by using acodebook of indexed values to retrieve a corresponding index), theindexed effective channel information is then communicated as a feedbacksignal over the feedback control channel to the transmitter station(step 406) and the receiver repeats the foregoing sequence during thenext design cycle (as indicated by the feedback line to step 402).

At the transmitter station, the feedback signals from the receiverstations are decoded to generate effective channel information for eachreceiver station, and this information is used to design transmitbeamformers w₁, w₂, . . . w_(m) using any arbitrary multi-user MIMOtechnique (step 408), such as zero-forcing beamforming. The transmitterthen uses each of the design transmit beamformers to precode one or morereference signals (e.g., RS₁, RS₂, etc.), and feeds forward theresulting N precoded reference signals (e.g., y₁=RS₁ w₁, y₂=RS₂w₂, etc.)to the receiver(s) (step 410), either directly or in quantized form.

Upon reception at a receiver, the N precoded reference signals aretested to detect the transmit beamformer that was intended for receiver,and to extract all transmit beamformers generated by the transmitter(step 412). With a first test (step 411), the precoding vector w_(UE)intended for the user equipment receiver is detected by selecting avector from a finite set of predetermined precoding vectors thatmaximizes the objective function

${\max\limits_{{j = 1},2,\ldots \mspace{14mu},N}{{v_{opt}^{H}y_{j}}}^{2}},$

where v_(opt) is the optimal blind receive beamformer initially designedby the receiver, y_(j) is the j^(th) received precoded reference signal(e.g., y_(j)=RS_(j)w_(j)), H is the channel matrix to the receiver inquestion. With a second test (step 413), the precoding vector matrix Wis derived by detecting which precoding vector was used to generate eachprecoded reference signal by selecting a vector from a finite set ofpredetermined precoding vectors that minimizes a second distancefunction min_(i)∥y−H^(H)w_(i)∥², where y is the subject precodedreference signal (e.g., y=RS₁w₁), H is the channel matrix to thereceiver in question, and w_(i) is used for each of the finite set ofpredetermined precoding vectors (e.g., w₁, w₂, etc.) stored at thereceiver.

Once the transmit beamformer information is extracted, the receiver usesthe extracted information to design the receive beamformer v_(i) for theMMSE receiver (step 414), and the receiver then uses the designedreceive beamformer v_(i) to receive OFDM symbol subcarriers that wereencoded with transmit beamformer w_(i) for the receiver (step 416).

The description provided thus far has been provided with reference toselected embodiments where multiple precoded reference signals are fedforward to the user equipment receivers. In these embodiments, eachreceiver is able to extract the transmit precoding vector informationfrom the precoded reference signals without having received priorknowledge of the specific precoding and beamforming algorithm used bythe transmitter, either by choosing from a predefined set of precodingvectors (e.g., w₁, w₂, . . . w_(m)) that is stored at each receiver, orby estimating the precoding vectors instead of doing a hypothesis testif they are arbitrary (i.e., they do not come from a pre-defined set butinstead are derived from an arbitrary continuous space). However,selected embodiments of the present invention provide for an even moreefficient reference signaling scheme for multi-user MIMO systems byusing structured precoded reference signals in combination withregularized zero-forcing beamforming techniques to effectively conveythe transmit precoding matrix W with a minimum of a single precodedreference signal. In other words, a mechanism is disclosed by whichinformation regarding an N×N transmission matrix (for any N) can be fedforward to each receiver by using just one precoded reference signal. Asa result, complete knowledge of the beamforming matrix may be providedto each receiver, but is done in such a way that size of the feedforward information does not scale with the size of N. As will beappreciated, the reliability or robustness of this algorithm can beimproved by adding more reference signals which is illustrated later on.

To illustrate the compact reference signaling scheme, reference is nowmade to the wireless communication system depicted in FIG. 2. Asdepicted, the transmitter base station 210 with multiple transmitantennas 226 communicates in a multi-user MIMO mode with multiple userequipment receivers 201.1-201.m, each of which has a multi-antenna array202.i. The transmitter base station 210 transmits via beamforming sothat the signal, denoted by s_(i), transmitted to a given user equipmentreceiver 201.i provides no interference to other receivers in thesystem. To accomplish this, the transmitter chooses the appropriatetransmit beamformers w_(i) based on the downlink channel informationu_(i) that has been fed back by each receiver over a feed back channel218.i. Downlink channel estimation is done at each receiver 201.i and isquantized using a known feedback codebook 211.i so that a codeword isselected from the codebook 211.i and fed back to the transmitter 210.Due to the imperfect channel knowledge at the transmitter 210, eachreceiver 201.i encounters interference from the transmissions to theother receivers in spite of the transmitter's effort to separate themulti-user streams.

In the single reference signal example, the vector design module 222uses a predetermined MU-MIMO algorithm—which in one embodiment can be aregularized zero-forcing beamforming (R-ZFBF) algorithm—to obtain userseparation. In one embodiment of a R-ZFBF algorithm, given apredetermined set (denoted as U) of candidate equivalent channelcodewords, the ‘m’ receivers feed back equivalent channel vectors(denoted as u₁, u₂, . . . ,u_(m)) from this set U. Based on the ‘m’equivalent channel vectors, the R-ZFBF algorithm is used to design thebeamforming matrix W using (X=[u₁ u₂ . . . u_(m)]), W=X[X^(H)X+αI]⁻¹,where I is an identity matrix and α is a scalar constant that provides asmoothing function to regularize the imperfection in effective channelestimates due to quantization or otherwise. The columns of the actualbeamforming matrix W are further normalized to be of unit norm.

With this approach, the optimal receiver/combiner at a receiver 201.i isan MMSE receiver which obtains knowledge of the beamforming matrix W byreceiving a single precoded reference signal on the forward downlinkchannel prior to data transmission using the compact feed forward schemedescribed herein. The approach exploits the fact that the precodingmatrix W corresponding to each unique combination of the possiblecodewords u_(i) is unique. Since each possible precoding matrix W isunique, the codewords in each possible X can be arranged by orderedindices so that the precoded reference signal or pilot that is sent onthe downlink broadcast channel uses a single predetermined column of thedesigned beamforming matrix W (e.g., the first column, or the secondcolumn, or the third column, etc.). When the precoded reference signalis detected, the extraction module 208.i in each receiver station 201.idetermines the precoding matrix W by hypothesis testing the precodedreference signal against the predetermined column (e.g., the firstcolumn) of all possible Ws (which are predetermined and locally stored).As can be seen, the extraction module 207.i (described above withreference to the multi-reference signal embodiment) is not needed todetect which precoding matrix W is signified by the single precodedreference signal.

Depending on whether the transmitter 210 uses the requested codewordu_(i) that was fed back as the transmit codeword c_(i) for a givenreceiver 201.i, two scenarios may arise. In the first scenario, if thetransmitter 210 does not use the codeword u_(i) requested by a givenreceiver 201.i and instead uses a different transmit codeword c_(i),then the receiver 201.i searches over all possible Ws. In the secondscenario, if the transmitter 210 uses the codeword u_(i) requested by agiven receiver 201.i for the transmit codeword c_(i), then the receiver201.i searches over only the Ws for which X contains u_(i)=c_(i). Byreducing the number of candidate codewords W that are searched, thecodeword estimation process and complexity may be reduced. In accordancewith selected embodiments, the search space may be further reduced byeliminating one or more highly improbable combinations.

In an example implementation, the receiver 201.i extracts the precodingmatrix W from the precoded reference signal by selecting the Wcorresponding to the predetermined column vector w_(i) which minimizesthe statistical test:

z _(test) =∥y−H ^(H) w ₁∥² , w _(t) in W_(S)(:,1),  [10]

where y is the received precoded reference signal (e.g., y=RS₁w₁H), H isthe MIMO downlink channel matrix, and W_(S)(:,1) is the space of thefirst columns of all Ws (though it will be appreciated that the secondcolumn could instead be used, or the third, or any predeterminedcolumn). Thus, the selected precoding matrix W is the estimate of thetransmit beamforming matrix used by the transmitter 210, and is used bythe MMSE receiver 209.i in the receiver 201.i to design the receivebeamforming vectors v_(i).

In an alternative embodiment for feeding forward transmission matrixinformation, each of the possible transmission matrices may beassociated with a unique vector from a feed forward vector codebook.With such a codebook, the reference signal may be encoded with thevector representative of the transmission matrix used. In that case, thetest in Equation [10] is modified to test the reference signal over allpossible vector codewords in the feed forward codebook (in lieu ofsearching over the first columns) with the objective of identifying thecodeword used for precoding. Once the codeword is identified, thetransmission matrix that it uniquely represents becomes known to thereceiver.

To illustrate the potential advantages of the single reference signalembodiment, consider the case of a 4×2 (or a 4×4) multi-user MIMO systemin which a codebook 211.i of size K is used at each receiver 201.i tofeed back effective channel codewords u. In this example, the totalnumber of candidate transmit beamforming matrices based on the possiblecodeword combinations is (K choose 4), meaning that the minimum bitlevel signaling required to convey the beamforming matrix to thereceivers is log₂(K choose 4). As a result, only one precoded pilotsymbol is required to determine the beamforming matrix, therebysignificantly reducing the control overhead required to convey theprecoding matrix information and enabling full MMSE to be performed atthe receiver. Of course, selected embodiments contemplate sending morethan one reference signal for increased robustness.

In connection with selected single reference signal embodiments of thepresent invention, FIG. 5 depicts an example flow 500 for a generalizedreference signaling scheme for a multi-user MIMO system. As depicted,the process starts (step 501) when the receiver station determines thetransmission channel profile based on the estimated channel informationfor the MIMO transmission channel (step 502). Based on the channelprofile information, the receiver station designs its optimal blindreceive beamformer v and selects an optimal codeword u=Hv (step 504) torepresent the effective channel to the receiver station. In effect, thecodeword u is the transmit beamformer w requested by the receiver. In anexample implementation, the vectors u and v may be jointly designed byselecting candidate values from a codebook of indexed precodingparameters that maximize a predetermined performance metric forestimating the receive SINR, where the metric is defined to reducequantization errors resulting from the codebook-based selection process.To account for the fact that the receiver station does not have priorknowledge about potential interference from other receiver stations, thereceiver station uses the computed vector v as an initial receivebeamforming vector. After quantizing the optimal codeword u (such as byusing a codebook of indexed values to retrieve a corresponding index),the indexed effective channel information is then communicated as afeedback signal over the feedback control channel to the transmitterstation (step 506) and the receiver repeats the foregoing sequenceduring the next design cycle (as indicated by the feedback line to step502).

At the transmitter station, the feedback signals from the receiverstations are decoded to generate effective channel information for eachreceiver station, and this information is used to design transmitbeamformers w₁, w₂, . . . w_(m) that will separate the receivers byusing a regularized zero-forcing beamforming (R-ZFBF) algorithm (step508). The designed transmit beamformers, taken together, are a transmitbeamforming matrix W. The transmitter then feeds forward to thereceivers a single precoded reference or pilot signal that is encodedusing the predetermined (first, second, third, etc . . . ) column of thedesigned transmit beamforming matrix W (step 510), either directly orusing a bit-level signaling scheme.

Upon reception at a receiver, the precoded reference signal is tested todetect the transmit beamforming matrix W that was used by thetransmitter (step 512). Each receiver determines the W by hypothesistesting the received precoding reference signal against thepredeteremined columns of all possible Ws (or a subset of possiblecodewords when the transmitter does not change the requested codewordc_(i) for the receiver). In the depicted example, the test (step 513)that is applied first selects a vector w_(t) from W_(S)(:,1) whichminimizes the test function z_(test)=∥y−H^(H)w_(t)∥². In this test, y isthe received precoded reference signal, H is the MIMO downlink channelmatrix, and W_(S)(:,1) is the space of the predetermined columns of allWs. In an alternative embodiment, a feed forward vector codebook may beused instead of the first column—that is a codebook/set of vectors maybe defined such that each transmission matrix is uniquely defined by adistinct vector in the set. The reference signaling may then be doneusing the codebook vector representative of the transmission matrixused, and the test above may be modified to search over all vectorcodewords in this codebook. The transmit beamforming matrix Wcorresponding to the selected vector w_(t) that minimizes the testfunction is the receiver's estimate of the beamforming matrix. Thisestimate of the transmit beamforming matrix W is used by the MMSEreceiver 209.i in the receiver 201.i to design the receive beamformingvectors v_(i). (step 514), and the receiver then uses the designedreceive beamformer v_(i) to receive data that were encoded with transmitbeamformer w_(i) for the receiver (step 516).

Once the transmission matrix W is identified at the receiving device, asecond test involves detecting which of the columns of W constitutes thebeamforming vector for the receiving device. This information isrequired to design the MMSE receiver 209.i, and can be obtained byidentifying the column that maximizes the metric, max_(j)|w_(j)^(H)Hv_(opt)|² where H is the channel matrix, and v_(opt) is the optimalblind receive beamformer. The j that maximizes the above function is thecolumn of the transmission matrix that is the beamforming vectorintended for itself.

By now it should be appreciated that there has been provided a forwardreference signaling method and system for a multiple input, multipleoutput (MIMO) space division multiple access (SDMA) systems that uses aplurality of precoded reference signals to convey transmit beamforminginformation. As disclosed, a transmitting device (e.g., a base station)receives effective channel information, such as a preferred precodingvector or information representative thereof, that is fed back from eachof a plurality of receiving devices (e.g., user equipment devices). Thetransmitting device uses the received effective channel information togenerate transmit beamforming vectors, such as by using a spatialseparation algorithm, such as zero-forcing beamforming, to outputtransmit beamforming vectors. Transmit beamforming vectors may begenerated by selecting transmit beamforming vectors from a defined setof transmit beamforming vectors. The transmit beamforming vectors areused to generate precoded reference signals by using each transmitbeamforming vector to encode a reference signal. For example, a firstreference signal may be encoded with a first transmit beamforming vectorto generate a first precoded reference signal that is designed for afirst receiving device, and a second reference signal may be encodedwith a second transmit beamforming vector to generate a second precodedreference signal that is designed for a second receiving device. Theprecoded reference signals may then be fed forward to a plurality ofreceiving devices where the precoded reference signals are received andused in generating receive beamforming vectors at each receiving device,where each receiving device extracts the plurality of transmitbeamforming vectors from the precoded reference signals and identifieswhich transmit beamforming vector is designed for said receiving devicewithout requiring additional information to be fed forward thatidentifies the transmit beamforming vector or precoded reference signalthat is designed for said receiving device. The extraction may beimplemented by applying a first test to the precoded reference signalsreceived at a receiving device to identify which transmit beamformingvector is designed for said receiving device, where the first testselects a reference signal from a finite set of transmit referencesignals y_(j) which maximizes a first projection measure|v_(opt)^(H)y_(j)|² and where v_(opt) is an optimal blind receive beamformingvector initially designed by said receiving device, y_(j) are theprecoded reference signals. In addition or in the alternative, theextraction may be implemented by applying a second test to the precodedreference signals received at a receiving device to identify theplurality of transmit beamforming vectors generated by the transmittingdevice, where the second test selects, for each precoded referencesignal, a transmit beamforming vector from a finite set of transmitbeamforming vectors w_(i) which minimizes a second distance measure∥y−H^(H)w_(i)∥², where y is a precoded reference signal and H is achannel matrix to said receiving device. With the second test, theplurality of transmit beamforming vectors are extracted by selectingtransmit beamforming vectors from a defined set of transmit beamformingvectors. After feeding forward the precoded reference signals, thetransmitting device may use the transmit beamforming vectors asweighting vectors for signals transmitted by the transmitting device tothe at least one of the plurality of receiving device. Thus, a referencesignaling framework and methodology are disclosed for feeding forwardreferences signals representing transmission matrix information formedwith an arbitrary algorithm that maps codewords fed back by the users tothe actual transmission matrix, where the reference signals aregenerated using N precoded pilots which are formed using N transmissionvectors selected from an arbitrary set of vectors unknown to thereceiving device. For example, when the N precoded pilots or referencesignals are formed by encoding N reference signals using thetransmission vectors to the N users, the N reference signals are testedat each receiving device in order to infer which of the N referencesignals is meant for the receiving device in question. Once detected,the receiver uses the N reference signals and the reference signaldesigned for the receiver to design the receiver beamformer.

In another embodiment, there is provided a forward reference signalingmethod and system for a MIMO SDMA system that uses a minimum of oneprecoded reference signal to convey transmit beamforming information. Asdisclosed, a transmitter receives effective channel information, such aspreferred precoding vector or information representative thereof, thatis fed back from a plurality of receiving devices, and then uses aspatial separation algorithm, such as zero-forcing beamforming, todesign a transmit beamforming matrix based on the received effectivechannel information, where the designed transmit beamforming matrix isselected from a defined set of transmit beamforming matrices. While anytype of zero-forcing beamforming may be used, in an example embodiment,a transmit beamforming matrix may be designed by designing a beamformingmatrix W using (X=[c₁c₂ . . . c_(m)]), W=X[X^(H)X+αI]⁻¹, where c₁, c₂, .. . c_(m) are candidate transmit beamforming vectors received from ‘m’receiving devices, α is a smoothing function constant and I is anidentity matrix. The designed transmit beamforming matrix is used togenerate one or more precoded reference signals by using all or part ofthe designed transmit beamforming matrix to encode one or more referencesignals. For a first example, a precoded reference signal may begenerated by encoding a first reference pilot with a predeterminedcolumn of the transmit beamforming matrix. In this case, the receivercan apply a hypothesis test to the received precoded reference signal toextract the transmit beamforming matrix by selecting a transmitbeamforming matrix from a finite set of candidate transmit beamformingmatrices, where the selected transmit beamforming matrix has apredetermined column w_(t) which minimizes a distance measurez_(test)=∥y−H^(H)w_(t)∥², where y is the received precoded referencesignal, and H is a MIMO downlink channel matrix to said receivingdevice. For a second example, a precoded reference signal may begenerated by encoding a first reference pilot with a first vector bselected from a predetermined set of vectors, where each vector in thepredetermined set of vectors uniquely represents a candidate transmitbeamforming matrix. In the second example, each transmit beamformingmatrix may be constructed as a plurality of columns arranged in apredetermined order that is known to the transmitting device and theplurality of receiving devices. In addition or in the alternative, eachtransmit beamforming matrix may be uniquely associated with one or moreunique identifying vectors from a feedforward vector codebook, whereeach unique identifying vector is generated with a Grassmanian-typecodebook. Alternatively, each unique identifying vector associated witha transmission beamforming matrix may be a predetermined column from thetransmission beamforming matrix. However defined, the unique identifyingvector which is associated with all or part of the designed transmitbeamforming matrix may be used to encode a first reference pilot,thereby generating a precoded reference signal. In this case, thereceiver can extract the transmit beamforming matrix by hypothesistesting the received precoded reference signal against a predeterminedset of vectors, where each vector in the predetermined set of vectorsuniquely represents a candidate transmit beamforming matrix. In anexample hypothesis test, the receiver extracts the transmit beamformingmatrix by selecting a transmit beamforming matrix from a finite set ofcandidate transmit beamforming matrices which uniquely corresponds to avector b which is selected by testing the precoded reference signal toidentify which vector b from the predetermined set of vectors minimizesa distance measure z_(test)=∥y−H^(H)b_(i)∥², where y is the receivedprecoded reference signal, H is a MIMO downlink channel matrix to saidreceiving device, and b_(i) is the predetermined set of vectors. Afterthe precoded reference signal is generated by the transmitter, it is fedforward to the receiving devices for use in generating receivebeamforming vectors at each receiving device, where each receivingdevice extracts the transmit beamforming matrix from at least theprecoded reference signal and identifies a transmit beamforming vectorthat is designed for said receiving device without requiring additionalinformation to be fed forward that identifies the transmit beamformingvector that is designed for said receiving device. As described herein,the designed transmit beamforming matrix can be extracted by hypothesistesting the received precoded reference signal against all possiblecandidate transmit beamforming matrices, or alternatively by hypothesistesting the received precoded reference signal against a subset of allpossible candidate transmit beamforming matrices when a transmitbeamforming vector for the receiving device is determined by theeffective channel information fed back to the transmitting device. Inaddition to extracting the designed transmit beamforming matrix from theprecoded reference signal(s), the receiving device also uses theprecoded reference signal(s) to identify a column from the designedtransmit beamforming matrix that is designed for the receiving device bytesting all columns of the generated transmit beamforming matrix, suchas by selecting a reference signal from a finite set of transmitreference signals y_(j) which maximizes a first objectivemeasure|v_(opt) ^(H)y_(j)|², where v_(opt) is an optimal blind receivebeamforming vector initially designed by said receiving device and y_(j)are the precoded reference signals. Thus, a single precoded referencesignal can be used at the receiving device to extract the designedtransmit beamforming matrix. Alternatively, a plurality of precodedreference signals can be used at the receiving device to extract thedesigned transmit beamforming matrix.

In yet another form, there is provided forward reference signalingmethod and system for a MIMO SDMA system that uses bit index values toconvey transmit beamforming information. As disclosed, a receivingdevice feeds back to a transmitting device a preferred precoding vectoror information representative thereof. Based at least in part on thepreferred precoding vector or information representative thereof, thetransmitting device generates a transmit beamforming matrix using aspatial separation algorithm, such as zero-forcing beamforming, and thentransmits over a feed forward channel one or more index bitsrepresentative of the generated transmit beamforming matrix. Using theindex bits, the receiving device retrieves the generated transmitbeamforming matrix from a finite set of candidate transmit beamformingmatrices, and uses the transmit beamforming matrix to generate a receivebeamforming vector at the receiving device. In selected embodiments, thetransmitting device and receiving device share a feed forward codebookcontaining the finite set of candidate transmit beamforming matrices.Thus, a reference signaling framework and methodology are disclosed forfeeding forward transmission matrix information using bits that arerepresentative of the transmission matrix used. When a receiver receivesindex bit values over the feed forward channel, the index bit values areevaluated against a candidate set of transmission matrices that aregenerated as a set of all possible combinations of precoding vectors orcodewords, wherein any precoding vector (codeword) could be used for thereceiving device independent of its feedback. To reduce the evaluationtime and complexity, the receiver can evaluate the index bit valuesagainst a candidate set of transmission matrices that are generated as aset of all possible combinations of precoding vectors (codewords)wherein one of the precoding vector (codeword) is fixed to be the onethat is fed back by the receiving device. In various embodiments, thecandidate set of transmission matrices may be compressed to removeunlikely matrices.

The methods and systems for using precoded reference signals toefficiently providing precoding matrix information to receivers in awireless, multi-user, multi-input, multiple output (MIMO) SDMA system asshown and described herein may be implemented in whole or in part withsoftware stored on a computer-readable medium and executed as a computerprogram on a general purpose or special purpose computer to performcertain tasks. For a hardware implementation, the elements used toperform various signal processing steps at the transmitter (e.g.,receiving and decoding quantized channel vector information, designingthe transmit beamforming vectors, generating precoded reference signals,selecting a feedforward index, preconditioning the precoded signals,coding and modulating the data, precoding the modulated signals, and soon) and/or at the receiver (e.g., recovering the transmitted signals,estimating channel information, feeding back quantized channel vectorinformation, demodulating and decoding the recovered signals, receivingand decoding quantized precoded reference signal information, extractingprecoding information from the precoded reference signals, designing thereceive beamforming vectors, and so on) may be implemented within one ormore application specific integrated circuits (ASICs), digital signalprocessors (DSPs), digital signal processing devices (DSPDs),programmable logic devices (PLDs), field programmable gate arrays(FPGAs), processors, controllers, micro-controllers, microprocessors,other electronic units designed to perform the functions describedherein, or a combination thereof In addition or in the alternative, asoftware implementation may be used, whereby some or all of the signalprocessing steps at each of the transmitter and receiver may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. It will be appreciated that theseparation of functionality into modules is for illustrative purposes,and alternative embodiments may merge the functionality of multiplesoftware modules into a single module or may impose an alternatedecomposition of functionality of modules. In any softwareimplementation, the software code may be executed by a processor orcontroller, with the code and any underlying or processed data beingstored in any machine-readable or computer-readable storage medium, suchas an on-board or external memory unit.

Although the described exemplary embodiments disclosed herein aredirected to various multi-user MIMO systems and methods for using same,the present invention is not necessarily limited to the exampleembodiments illustrate herein. For example, various embodiments of aMIMO precoding system and design methodology disclosed herein may beimplemented in connection with various proprietary or wirelesscommunication standards, such as IEEE 802.16e, 3GPP-LTE, DVB and othermulti-user MIMO systems. Thus, the particular embodiments disclosedabove are illustrative only and should not be taken as limitations uponthe present invention, as the invention may be modified and practiced indifferent but equivalent manners apparent to those skilled in the arthaving the benefit of the teachings herein. Accordingly, the foregoingdescription is not intended to limit the invention to the particularform set forth, but on the contrary, is intended to cover suchalternatives, modifications and equivalents as may be included withinthe spirit and scope of the invention as defined by the appended claimsso that those skilled in the art should understand that they can makevarious changes, substitutions and alterations without departing fromthe spirit and scope of the invention in its broadest form.

Benefits, other advantages, and solutions to problems have beendescribed above with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any element(s) that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as a critical, required, or essentialfeature or element of any or all the claims. As used herein, the terms“comprises,” “comprising,” or any other variation thereof, are intendedto cover a non-exclusive inclusion, such that a process, method,article, or apparatus that comprises a list of elements does not includeonly those elements but may include other elements not expressly listedor inherent to such process, method, article, or apparatus.

1-40. (canceled)
 41. A forward reference signaling method for a multipleinput, multiple output (MIMO) space division multiple access (SDMA)system, comprising: receiving at a transmitting device effective channelinformation from a plurality of receiving devices by receiving apreferred precoding vector or information representative thereof fromeach of the plurality of receiving devices; generating a plurality oftransmit beamforming vectors based on the effective channel informationusing a spatial separation scheme which selects transmit beamformingvectors from a defined set of transmit beamforming vectors; generatingprecoded reference signals by using each transmit beamforming vector toencode a reference signal; and feeding forward the precoded referencesignals to a plurality of receiving devices for use in generatingreceive beamforming vectors at each receiving device, where eachreceiving device extracts the plurality of transmit beamforming vectorsfrom the precoded reference signals and identifies which transmitbeamforming vector is designed for said receiving device withoutrequiring additional information to be fed forward that identifies thetransmit beamforming vector or precoded reference signal that isdesigned for said receiving device.
 42. The method of claim 41, wheregenerating precoded reference signals comprises: encoding a firstreference signal with a first transmit beamforming vector to generate afirst precoded reference signal that is designed for a first receivingdevice; and encoding a second reference signal with a second transmitbeamforming vector to generate a second precoded reference signal thatis designed for a second receiving device.
 43. The method of claim 41,where generating precoded reference signals comprises encoding a firstreference pilot with a predetermined one of the plurality of transmitbeamforming vectors.
 44. The method of claim 41, where generating theplurality of transmit beamforming vectors comprises using a spatialseparation algorithm to design a transmit beamforming matrix W using(X=[c₁c₂ . . . c_(m)]), W=X[X^(H)X+αI]⁻¹, where c₁, c₂, . . . c_(m) arecandidate transmit beamforming vectors received from ‘m’ receivingdevices, α is a smoothing function constant and I is an identity matrix.45. A forward reference signaling method for a multiple input, multipleoutput (MIMO) space division multiple access (SDMA) system, comprising:receiving at a transmitting device effective channel information from aplurality of receiving devices; generating a plurality of transmitbeamforming vectors based on the effective channel information;generating precoded reference signals by using each transmit beamformingvector to encode a reference signal; and feeding forward the precodedreference signals to a plurality of receiving devices for use ingenerating receive beamforming vectors at each receiving device, whereeach receiving device identifies its own effective channel withoutrequiring additional information to be fed forward that identifies thetransmit beamforming vector or precoded reference signal that isdesigned for said receiving device.
 46. The method of claim 45, wheregenerating precoded reference signals comprises: encoding a firstreference signal with a first transmit beamforming vector to generate afirst precoded reference signal that is designed for a first receivingdevice; and encoding a second reference signal with a second transmitbeamforming vector to generate a second precoded reference signal thatis designed for a second receiving device.
 47. The method of claim 45,where generating precoded reference signals comprises encoding a firstreference pilot with a predetermined one of the plurality of transmitbeamforming vectors.
 48. The method of claim 45, where generating theplurality of transmit beamforming vectors comprises using a spatialseparation algorithm to design a transmit beamforming matrix W using(X=[c₁c₂ . . . c_(m)]), W=X[X^(H)X+αI]⁻¹, where c₁, c₂, . . . c_(m) arecandidate transmit beamforming vectors received from ‘m’ receivingdevices, α is a smoothing function constant and I is an identity matrix.49. The method of claim 45, where generating the plurality of transmitbeamforming vectors comprises using spatial separation algorithm todesign a transmit beamforming matrix comprises designing a beamformingmatrix W=[w₁w₂ . . . w_(m)] such that w_(i)={tilde over (w)}_(i)/∥{tildeover (w)}_(i)∥ and{tilde over (w)} _(i) ^(H) u _(j)≧γ₁, if i=j{tilde over (w)} _(i) ^(H) u _(j)≦γ₂, if i≠j where γ₁>0 and γ₂ areconstants such that γ₂<<γ₁ and u₁, u₂, . . . u_(m) are candidatetransmit beamforming vectors received from ‘m’ receiving devices.
 50. Areceiving device signaling method in a multiple input, multiple output(MIMO) space division multiple access (SDMA) system, comprising: feedingback to a transmitting device effective channel information for use bythe transmitting device, along with effective channel information fromother receiving devices, in generating a plurality of transmitbeamforming vectors; receiving from the transmitting device precodedreference signals that are generated from the plurality of transmitbeamforming vectors; and identifying from the precoded reference signalsthe receive beamforming vector for the receiving device withoutrequiring additional information to be fed forward that identifies thetransmit beamforming vector that is designed for said receiving device.51. The method of claim 50, where identifying the receive beamformingvector comprises: extracting at the receiving device the plurality oftransmit beamforming vectors from the precoded reference signals; andusing the plurality of transmit beamforming vectors to generate areceive beamforming vector at the receiving device.
 52. The method ofclaim 50, further comprising applying a first test to the precodedreference signals received to identify which transmit beamforming vectoris designed for said receiving device, where the first test comprisesselecting a reference signal from a finite set of transmit referencesignals y_(j) which maximizes a first objective measure|v_(opt)^(H)y_(j)|², where v_(opt) is an optimal blind receive beamformingvector initially designed by said receiving device and y_(j) are theprecoded reference signals.
 53. The method of claim 50, furthercomprising applying a second test to the precoded reference signalsreceived at a receiving device to identify each of the plurality oftransmit beamforming vectors generated by the transmitting device, wherethe second test comprises selecting from the precoded reference signalsa transmit beamforming vector from a finite set of transmit beamformingvectors w_(i) which minimizes a distance measure ∥y−H^(H)w_(i)∥², wherey are the precoded reference signals and H is a channel matrix to saidreceiving device.
 54. The method of claim 50, where feeding backeffective channel information comprises feeding back a preferredprecoding vector from the receiving device.
 55. The method of claim 51,where extracting the plurality of transmit beamforming vectors comprisesselecting a transmit beamforming matrix from a defined set of transmitbeamforming matrices.
 56. The method of claim 55, further comprisingidentifying at the receiving device a column from the selected transmitbeamforming matrix that is designed for the receiving device by testingall columns of the transmit beamforming matrix.
 57. The method of claim51, where extracting the plurality of transmit beamforming vectors fromthe precoded reference signals comprises hypothesis testing the precodedreference signals received at the receiving device against apredetermined set of vectors, where each vector in the predetermined setof vectors uniquely represents a candidate transmit beamforming matrix.